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llama.cpp
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Minor stats report cosmetic changes

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Ed Addario 2025-10-29 07:59:40 +00:00
parent 86fabce58d
commit 6ff0a79e54
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GPG Key ID: E7875815A3230993
1 changed files with 8 additions and 8 deletions
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16
tools/imatrix/imatrix.cpp
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@ -150,7 +150,7 @@ static std::vector<float> compute_tensor_averages(const Stats & tstats) {
} else { } else {
// Mean // Mean
for (size_t m = 0; m < n_mat; ++m) { for (size_t m = 0; m < n_mat; ++m) {
const float c = (float)tstats.counts[m]; const auto c = (float)tstats.counts[m];
const size_t off = m * row; const size_t off = m * row;
if (c <= 0.0f) { if (c <= 0.0f) {
vec.insert(vec.end(), row, 0.0f); // zero-fill rows for experts with zero count to preserve shape vec.insert(vec.end(), row, 0.0f); // zero-fill rows for experts with zero count to preserve shape
@ -215,7 +215,7 @@ static bool compute_vector_statistics(std::vector<tensor_statistics> & tstats, c
double sqr_sum = 0.0; double sqr_sum = 0.0;
for (const float v : activations) { sqr_sum += (double)v * (double)v; } for (const float v : activations) { sqr_sum += (double)v * (double)v; }
double variance = sqr_sum / (double)activations.size() - (double)mean * (double)mean; double variance = sqr_sum / (double)activations.size() - (double)mean * (double)mean;
if (variance < 0.0) { variance = 0.0; } variance = std::max(variance, 0.0);
const float std_deviation = std::sqrt((float)variance); const float std_deviation = std::sqrt((float)variance);
float entropy = 0.0f; float entropy = 0.0f;
@ -1327,7 +1327,7 @@ static bool show_statistics(const common_params & params) {
LOG_INF("\n%6s\t%18s\t%13s\t%8s\t%8s\t%7s\t%15s\t%13s\t%11s\t%8s\t%5s\t%10s\n", LOG_INF("\n%6s\t%18s\t%13s\t%8s\t%8s\t%7s\t%15s\t%13s\t%11s\t%8s\t%5s\t%10s\n",
"Layer", "Layer",
"Tensor", "Tensor",
legacy_mode ? "Σ(Act²)" : "L₂ Norm", legacy_mode ? "Σ E[Act²]" : "L₂ Norm",
"Min", "Min",
"Max", "Max",
"μ", "μ",
@ -1356,7 +1356,7 @@ static bool show_statistics(const common_params & params) {
const float h_norm = tstat.elements > 1 ? 100.0f * (tstat.entropy / std::log2((float) tstat.elements)) : 0.0f; const float h_norm = tstat.elements > 1 ? 100.0f * (tstat.entropy / std::log2((float) tstat.elements)) : 0.0f;
const float ecs = 100.0f * std::exp(-0.01f * tstat.l2_norm) * std::pow(std::fabs(tstat.cossim), 10.0f); const float ecs = 100.0f * std::exp(-0.01f * tstat.l2_norm) * std::pow(std::fabs(tstat.cossim), 10.0f);
LOG_INF("%5s\t%-20s\t%11.2f\t%10.4f\t%10.4f\t%8.2f\t%8.2f\t%7d\t%10.2f%%\t%10.4f\t%6.2f%%\t%10.4f\n", LOG_INF("%5s\t%-20s\t%11.4f\t%10.4f\t%10.4f\t%8.4f\t%8.4f\t%7d\t%10.2f%%\t%10.4f\t%6.2f%%\t%10.4f\n",
layer.c_str(), layer.c_str(),
name.c_str(), name.c_str(),
legacy_mode ? tstat.sum_values : tstat.l2_norm, legacy_mode ? tstat.sum_values : tstat.l2_norm,
@ -1392,7 +1392,7 @@ static bool show_statistics(const common_params & params) {
LOG_INF("\nComputing layer statistics (%zu layers)\n", layers); LOG_INF("\nComputing layer statistics (%zu layers)\n", layers);
LOG_INF("\n%6s\t%13s\t%6s\t%11s\t%6s\n", LOG_INF("\n%6s\t%13s\t%6s\t%11s\t%6s\n",
"Layer", "Layer",
legacy_mode ? "Σ(Act²)" : "L₂ Norm", legacy_mode ? "Σ E[Act²]" : "L₂ Norm",
"ZD", "ZD",
"CosSim", "CosSim",
legacy_mode ? "" : "ECS"); legacy_mode ? "" : "ECS");
@ -1402,19 +1402,19 @@ static bool show_statistics(const common_params & params) {
LOG_INF("=========================================================\n"); LOG_INF("=========================================================\n");
} }
for (const auto & [layer, stats] : ls) { for (const auto & [layer, stats] : ls) {
if (layer < 0 || stats.n == 0) continue; if (layer < 0 || stats.n == 0) { continue; }
const auto lcs = layer_cossim.find(layer); const auto lcs = layer_cossim.find(layer);
const float layer_cs = lcs != layer_cossim.end() ? lcs->second : 0.0f; const float layer_cs = lcs != layer_cossim.end() ? lcs->second : 0.0f;
const auto ll2n = layer_l2_norm.find(layer); const auto ll2n = layer_l2_norm.find(layer);
const float layer_l2n = ll2n != layer_l2_norm.end() ? ll2n->second : 0.0f; const float layer_l2n = ll2n != layer_l2_norm.end() ? ll2n->second : 0.0f;
if (legacy_mode) { if (legacy_mode) {
LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\n", LOG_INF("%5d\t%11.4f\t%6.2f%%\t%11.4f\n",
layer, layer,
stats.layer_sum, stats.layer_sum,
100.0f * stats.layer_zd / stats.n, 100.0f * stats.layer_zd / stats.n,
layer_cs); layer_cs);
} else { } else {
LOG_INF("%5d\t%11.2f\t%6.2f%%\t%11.4f\t%8.4f\n", LOG_INF("%5d\t%11.4f\t%6.2f%%\t%11.4f\t%8.4f\n",
layer, layer,
layer_l2n, layer_l2n,
100.0f * stats.layer_zd / stats.n, 100.0f * stats.layer_zd / stats.n,